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I think many of those who use computers to handicap races hope to beat the races (generically) rather than beating each specific race. The broad brush strokes derived from AI, ML, and NN tend to be useful generically, but not so useful when applied to individual races. Specifically, it is way easier to develop models that will predict X wins per howevermany races, with a probable (hopefully positive) ROI in some range, than it is to predict that Horse A will beat Horses B, C, D, E, F, and G in the next race.
Toward that end, qualitative (rather than quantitative) data (trip notes, observation, many others) is less useful because it is ambiguous and event-specific. Essential when betting individual races, not so much so when betting a (relatively) high volume of races.
Different tactics for different strategies. The trick is not to confuse the strategies (or the tactics needed to implement the selected strategy).
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